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A semiautomatic model-based approach to the view planning problem for high-resolution active triangulation 3-D inspection systems is presented. First, a comprehensive, general, high-fidelity model of such systems is developed for the evaluation of configurations with respect to a model of task requirements, with a bounded scalar performance metric. The design process is analyzed, and the automated view planning problem is formulated only for the critically difficult aspects of design. A particle swarm optimization algorithm is applied to the latter portion, including probabilistic modeling of positioning error, using the performance metric as an objective function. The process leverages human strengths for the high-level design, refines low-level details mechanically, and provides an absolute measure of task-specific performance of the resulting design specification. The system model is validated, allowing for a reliable rapid design cycle entirely in simulation. Parameterization of the optimization algorithm is analyzed and explored empirically for performance.Index Terms-Inspection, laser scanner, range camera, view planning.

An automatic method for solving the problem of view planning in high-resolution industrial inspection is presented. The method's goal is to maximize the visual coverage, and to minimize the number of cameras used for inspection. Using a CAD model of the object of interest, we define the scenepoints and the viewpoints, with the later being the solution space. The problem formulation accurately encapsulates all the vision-and task-related requirements of the design process for inspection systems. We use a graph-based approach to formulate a solution for the problem. The solution is implemented as a greedy algorithm, and the method is validated through experiments.

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